Literature DB >> 21926009

Influence of I(Ks) heterogeneities on the genesis of the T-wave: a computational evaluation.

David U J Keller1, Daniel L Weiss, Olaf Dossel, Gunnar Seemann.   

Abstract

Despite the commonly accepted notion that action potential duration (APD) is distributed heterogeneously throughout the ventricles and that the associated dispersion of repolarization is mainly responsible for the shape of the T-wave, its concordance and exact morphology are still not completely understood. This paper evaluated the T-waves for different previously measured heterogeneous ion channel distributions. To this end, cardiac activation and repolarization was simulated on a high resolution and anisotropic biventricular model of a volunteer. From the same volunteer, multichannel ECG data were obtained. Resulting transmembrane voltage distributions for the previously measured heterogeneous ion channel expressions were used to calculate the ECG and the simulated T-wave was compared to the measured ECG for quantitative evaluation. Both exclusively transmural (TM) and exclusively apico-basal (AB) setups produced concordant T-waves, whereas interventricular (IV) heterogeneities led to notched T-wave morphologies. The best match with the measured T-wave was achieved for a purely AB setup with shorter apical APD and a mix of AB and TM heterogeneity with M-cells in midmyocardial position and shorter apical APD. Finally, we probed two configurations in which the APD was negatively correlated with the activation time. In one case, this meant that the repolarization directly followed the sequence of activation. Still, the associated T-waves were concordant albeit of low amplitude.
© 2011 IEEE

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Year:  2011        PMID: 21926009     DOI: 10.1109/TBME.2011.2168397

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  21 in total

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Journal:  Ann Biomed Eng       Date:  2012-05-31       Impact factor: 3.934

Review 2.  Cardiac ischemia-insights from computational models.

Authors:  Axel Loewe; Eike Moritz Wülfers; Gunnar Seemann
Journal:  Herzschrittmacherther Elektrophysiol       Date:  2018-01-05

3.  Regional segmentation of ventricular models to achieve repolarization dispersion in cardiac electrophysiology modeling.

Authors:  L E Perotti; S Krishnamoorthi; N P Borgstrom; D B Ennis; W S Klug
Journal:  Int J Numer Method Biomed Eng       Date:  2015-04-28       Impact factor: 2.747

4.  The functional role of electrophysiological heterogeneity in the rabbit ventricle during rapid pacing and arrhythmias.

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Journal:  Am J Physiol Heart Circ Physiol       Date:  2013-02-22       Impact factor: 4.733

5.  A computational model of rabbit geometry and ECG: Optimizing ventricular activation sequence and APD distribution.

Authors:  Robin Moss; Eike M Wülfers; Raphaela Lewetag; Tibor Hornyik; Stefanie Perez-Feliz; Tim Strohbach; Marius Menza; Axel Krafft; Katja E Odening; Gunnar Seemann
Journal:  PLoS One       Date:  2022-06-30       Impact factor: 3.752

6.  Application of stochastic phenomenological modelling to cell-to-cell and beat-to-beat electrophysiological variability in cardiac tissue.

Authors:  John Walmsley; Gary R Mirams; Joe Pitt-Francis; Blanca Rodriguez; Kevin Burrage
Journal:  J Theor Biol       Date:  2014-11-04       Impact factor: 2.691

Review 7.  Computational models in cardiology.

Authors:  Steven A Niederer; Joost Lumens; Natalia A Trayanova
Journal:  Nat Rev Cardiol       Date:  2019-02       Impact factor: 32.419

8.  Anatomically accurate high resolution modeling of human whole heart electromechanics: A strongly scalable algebraic multigrid solver method for nonlinear deformation.

Authors:  Christoph M Augustin; Aurel Neic; Manfred Liebmann; Anton J Prassl; Steven A Niederer; Gundolf Haase; Gernot Plank
Journal:  J Comput Phys       Date:  2016-01-15       Impact factor: 3.553

9.  Computational assessment of drug-induced effects on the electrocardiogram: from ion channel to body surface potentials.

Authors:  Nejib Zemzemi; Miguel O Bernabeu; Javier Saiz; Jonathan Cooper; Pras Pathmanathan; Gary R Mirams; Joe Pitt-Francis; Blanca Rodriguez
Journal:  Br J Pharmacol       Date:  2013-02       Impact factor: 8.739

10.  Simulation Methods and Validation Criteria for Modeling Cardiac Ventricular Electrophysiology.

Authors:  Shankarjee Krishnamoorthi; Luigi E Perotti; Nils P Borgstrom; Olujimi A Ajijola; Anna Frid; Aditya V Ponnaluri; James N Weiss; Zhilin Qu; William S Klug; Daniel B Ennis; Alan Garfinkel
Journal:  PLoS One       Date:  2014-12-10       Impact factor: 3.240

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